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Application of a stochastic damage model to predict the variability of creep behavior for asphalt mixtures

Authors :
Qipeng Zhang
Xingyu Gu
Jia Liang
Zilu Yu
Qiao Dong
Jiwang Jiang
Source :
Case Studies in Construction Materials, Vol 18, Iss , Pp e02078- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

The creep test is used as the main method of evaluating the rutting resistance of asphalt mixtures, but the variability has rarely been studied. Based on creep tests, this study investigated the stochastic nature of the mixture creep through mechanical modeling. First, creep tests were carried out on mixtures under different conditions. Consequently, the creep behavior was characterized using a fractional creep damage model (FCDM) and a variability analysis was performed. Second, a proposed creep stochastic damage model (CSDM), developed using a meso-mechanical approach, was utilized to characterize the variability behavior of the damage evolution, and the range of variation in damage evolution was predicted within a certain confidence interval. Subsequently, combined with FCDM, the variation of mixtures during creep was predicted. This study confirmed that the creep variability of mixtures is related to rutting resistance, and the better rutting resistance implies lower variability. The validation and prediction results show that the CSDM can well describe the stochasticity of damage, and that the variability of creep behavior for asphalt mixtures can be well predicted on the basis of the stochasticity of damage evolution. The physical mechanism of damage stochasticity in the mixture creep was clearly demonstrated on the mesoscopic scale.

Details

Language :
English
ISSN :
22145095
Volume :
18
Issue :
e02078-
Database :
Directory of Open Access Journals
Journal :
Case Studies in Construction Materials
Publication Type :
Academic Journal
Accession number :
edsdoj.8b2ae5539014612bb8d61385f25d5ce
Document Type :
article
Full Text :
https://doi.org/10.1016/j.cscm.2023.e02078